The reconstruction of two-dimensional image datasets from one-dimensional image datasets or of three-dimensional image datasets from two-dimensional image datasets has long been known in X-ray imaging, for which different reconstruction methods are known, for example filtered back projection and iterative reconstruction. The projection images are recorded in such cases in a chronological sequence from different projection angles, whereby X-ray emitter and detector mostly describe an orbital trajectory.
A problem always arises if, during a recording process, i.e. from the recording of the first projection image through to the recording of the last projection image, the attenuation values at specific points of the target region change over time. This will be explained in more detail with reference to an example.
Strokes are the third most frequent cause of death in Western countries. Intra-arterial thrombolysis can be used for their treatment in which a medicament is administered through a catheter into a brain artery, with the aid of which the thrombus can be removed or which dissolves the latter. In such cases it is helpful, shortly before and/or during and/or after the intervention, to carry out a tomographic blood flow measurement through perfusion imaging.
In such cases current known methods are perfusion CT imaging and perfusion MR imaging, in which a contrast agent is injected and a series of image datasets are recorded in order to observe the spreading out of the contrast agent in the patient's vascular system. Time-attenuation curves can then be identified from the image datasets, from which the blood flow, in the example the cerebral blood flow, is determined.
Since these types of interventions are frequently undertaken with the support of a C-arm X-ray device, for example an angiography system, it would be of great advantage for the workflow in the interventions if the perfusion imaging were able to be carried out with a C-arm.
For standard reconstruction methods however it is a prerequisite that the attenuation values remain at least essentially constant over time during the recording of the projection images. Since the rotation time of the C-arm with the X-ray emitter and the detector, which can typically amount to between three and five seconds, is however significantly longer than that of a CT device, which can typically amount to 0.5 seconds, artifacts are produced in the slower C-arm recordings, which are the result of changes in the attenuation values caused by the inflow or outflow respectively of contrast agent. These falsify the results however.
To solve these problems there are already two known solutions in the prior art.
It has thus been proposed that a dynamic approach to reconstruction be selected in order to reconstruct a perfusion dataset from projection images recorded with a C-arm X-ray device. This approach is based on a similar method to algebraic reconstruction techniques and is described in articles by Serowy, S. et al., “A Jacobi-like Solution to the Model Based Tomographic X-Ray Perfusion Imaging”, Proc. IEEE NSS/MIC, 2007, 4, pages 3085 to 3088, and also C. Neukirchen and S. Hohmann, “An Iterative Approach for Model-Based Tomographic Perfusion Estimation”. Proc. Fully-3D, 2007, pages 104 to 107. However this method is extremely slow and thereby inefficient. In addition the proposed optimization methods can create solutions which only correspond to local minima and thus deliver an unsatisfactory image quality.
It has further been proposed that a dynamic reconstruction algorithm be selected which builds on the filtered back projection to reduce the inconsistency by a temporal interpolation method. This method is described in articles by P. Montes and G. Lauritsch, “A Temporal Interpolation Approach for Dynamic Reconstruction in Perfusion CT”, Med. Phys. 2007, 34, pages 3077 to 3092, and also A. Fieselmann et al., “A Dynamic Reconstruction Approach for Cerebral Blood Flow Quantification with an Interventional C-arm CT”, Proc. IEEE ISBI, 2010, pages 53 to 56. This method too is rather slow and is not optimally suited to typical recording geometries of C-arm angiography systems, in which the C-arm rotates alternately in different directions.